The intersection of artificial intelligence (AI) and cryptocurrency is generating waves in the tech world, and blockchain AI projects have quickly become the talk of the industry. In recent years, AI crypto tokens have seen market caps soar to over $1 billion, but despite this massive investor interest, the demand from end-users remains underwhelming. So, the pressing question for investors is: how do you figure out if an AI crypto project is worth investing in?
In this article, we’ll explore the factors that make a blockchain AI project a good investment, featuring insights from industry leaders and offering practical advice on evaluating these emerging technologies. Let’s break down what you need to consider when evaluating AI crypto projects.
The Growing Demand for GPUs: Decentralised Blockchain Solutions to the Rescue
One of the primary challenges facing the AI industry today is the increasing demand for Graphical Processing Units (GPUs). These powerful chips are essential for training AI models, but centralized cloud computing systems—like AWS or Google Cloud—are struggling to keep up with demand. This opens the door for decentralized blockchain AI projects to address the GPU shortage.
Guarav Sharma, Chief Technology Officer of AI project IO, explained that AI developers are often faced with long waits and high costs when trying to acquire enough GPUs for their models. Sharma recounted his own experience working in the hotel industry, where he struggled to get enough GPU power from Amazon to train his AI model. Centralized cloud services simply could not meet the demand for GPUs in a timely manner.
This is where blockchain AI can shine. By decentralizing the availability of GPUs, platforms like IO can create a marketplace where GPU providers and AI clients can connect directly. This eliminates the bottlenecks caused by centralised services, offering faster and more efficient access to the resources required for AI development.
If you’re looking to invest in an AI crypto project, understanding whether they offer decentralised computing power like this could be a game-changer. Blockchain projects with strong GPU marketplaces are addressing a critical gap in the AI ecosystem and may be better positioned for long-term success.
The Power of the Team: Invest in Proven Track Records
One of the biggest red flags when evaluating an AI blockchain project is the team behind it. Guarav Sharma cautioned investors to be wary of projects that claim to create the next big AI model with minimal teams or little experience.
Good AI projects are built by experienced teams with a proven track record. If a project’s team includes engineers who have worked with leading tech companies but lacks tangible evidence of previous successful AI projects, that’s a significant risk.
Key things to look out for:
- Past achievements: Has the team created valuable projects or models before?
- Transparency: Does the project open-source its code for public scrutiny?
- Audits: Are there regular third-party audits to verify the quality and progress of the project?
By focusing on projects that offer open-source code and allow for third-party audits, you can ensure that the project has nothing to hide and is serious about its goals.
Distinguishing Real AI from Fake AI Projects
As AI blockchain projects are on the rise, it’s becoming increasingly difficult to separate genuine AI-driven solutions from those that claim to use AI but are actually relying heavily on human intervention. Kartin Wong, co-founder of ORA, emphasized that many projects claim to offer AI but use humans to check the results. This can lead to an inflated sense of the technology’s capabilities.
So, how can investors identify a real AI project from a fake one?
Real AI Projects:
- Autonomous behaviour: If the system acts in ways that humans cannot replicate or keep up with, it’s likely AI.
- Speed and performance: Real AI can answer questions and generate results faster than any human team could.
- Clear functionality: AI should be able to handle complex tasks autonomously, not just replicate human efforts.
For example, Wong pointed to ChatOLM, a chatbot created on ORA’s platform, which outperformed humans in answering questions. If you’re considering investing in a blockchain AI project, test the product yourself. A real AI product will demonstrate its value immediately.
Prediction Markets and Blockchain AI: A Future Need
Another interesting use case for blockchain AI is in prediction markets. According to Wong, platforms like Polymarket, which runs on blockchain, currently struggle because they rely on human judgment to resolve betting outcomes. This is where blockchain AI comes in.
AI can provide the oracle layer that solves these problems. With AI-driven oracles, blockchain prediction markets can receive real-time answers that are accurate and not subject to human bias. This presents an opportunity for blockchain AI to become the backbone of decentralised prediction markets.
Additionally, platforms like ORA are pioneering the Initial Model Offering (IMO), where AI models can issue tokens to raise funds for their training. Token holders can then benefit from the success of the model. The transparency provided by open-source models and tokenisation is a unique feature that sets blockchain AI apart from traditional AI development.
Decentralized AI: The Key to Truly Autonomous Systems
As Ron Chan, co-founder of Inference Labs, pointed out, decentralised blockchain AI is the only way to achieve truly autonomous AI systems. Centralized AI systems are often developed to serve the needs of large corporations, whereas decentralized AI can evolve freely, driven by market demand and community input.
The big advantage of decentralised AI is that it can evolve quickly to meet the needs of a human-centric market. Blockchain allows for the proof of inference, which means the ability to prove that a specific result or answer came from a particular AI model. This capability is essential for verifying the autonomy of an AI system.
For investors, the key takeaway here is that projects promising decentralised AI are setting the stage for a new wave of AI development. AI autonomy isn’t just a theoretical concept; it’s happening now, and blockchain is the vehicle for its realisation.
Consumer-Facing Blockchain AI Apps: Are We There Yet?
As blockchain AI technologies evolve, many are eager to know when they will be available for everyday users. While current consumer-facing applications are still limited, industry leaders are hopeful about the future.
For instance, Wong mentioned OLMChat, a chat application built on blockchain and AI, while Chan discussed applications for aircraft tracking and liquid staking powered by AI. These projects may not have the massive user bases of ChatGPT or other mainstream tools, but they are proof that blockchain AI can solve real-world problems.
While the future benefits of blockchain AI may take some time to be fully realised, the current applications demonstrate the potential of these technologies to impact industries far beyond cryptocurrency.
Conclusion: Evaluating Blockchain AI Projects
Investing in AI crypto projects requires a blend of cautious optimism and thorough due diligence. Here are the key takeaways to consider:
- GPU demand: Is the project solving real-world problems like GPU shortages with decentralised solutions?
- The team: Does the team have a proven track record and the technical expertise needed to succeed?
- Transparency: Are the AI models open-source and regularly audited?
- Real AI vs. Fake AI: Can you distinguish between genuine AI and human-assisted models?
- Decentralisation: Is the project aiming to create autonomous AI with decentralised systems?
The AI crypto revolution may be in its early stages, but by keeping these criteria in mind, you can make informed decisions and potentially reap the rewards as these technologies evolve.
